The Experts below are selected from a list of 306579 Experts worldwide ranked by ideXlab platform
Yue Joseph Wang - One of the best experts on this subject based on the ideXlab platform.
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Blind Source Separation with Pattern Expression NMF
Lecture Notes in Computer Science, 2006Co-Authors: Junying Zhang, Zhang Hong-yi, Le Wei, Yue Joseph WangAbstract:Independent component analysis (ICA) is a widely applicable and effective approach in blind source separation (BSS) for basic ICA model, but with limitations that sources should be statistically independent, while more common situation is BSS for non-negative linear (NNL) model where observations are linear combinations of non-negative sources with non-negative coefficients and sources may be statistically dependent. By recognizing the fact that BSS for basic ICA model corresponds to matrix factorization problem, in this paper, a novel idea of BSS for NNL model is proposed that the BSS for NNL come'[ sponds to a non-negative matrix factorization problem and the non-negative matrix factorization (NMF) technique is utilized. For better Expression of the Patterns of the sources, the NMF is further extended to Pattern Expression NMF (PE-NMF) and its algorithm is presented. Finally, the experimental results are presented which show the effectiveness and efficiency of the PE-NMF to BSS for a variety of applications which follow NNL model.
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ISNN (1) - Blind source separation with Pattern Expression NMF
Advances in Neural Networks - ISNN 2006, 2006Co-Authors: Junying Zhang, Zhang Hong-yi, Le Wei, Yue Joseph WangAbstract:Independent component analysis (ICA) is a widely applicable and effective approach in blind source separation (BSS) for basic ICA model, but with limitations that sources should be statistically independent, while more common situation is BSS for non-negative linear (NNL) model where observations are linear combinations of non-negative sources with non-negative coefficients and sources may be statistically dependent. By recognizing the fact that BSS for basic ICA model corresponds to matrix factorization problem, in this paper, a novel idea of BSS for NNL model is proposed that the BSS for NNL corresponds to a non-negative matrix factorization problem and the non-negative matrix factorization (NMF) technique is utilized. For better Expression of the Patterns of the sources, the NMF is further extended to Pattern Expression NMF (PE-NMF) and its algorithm is presented. Finally, the experimental results are presented which show the effectiveness and efficiency of the PE-NMF to BSS for a variety of applications which follow NNL model.
Qi Qi - One of the best experts on this subject based on the ideXlab platform.
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A conserved sequence in caveolin‐1 is both necessary and sufficient for caveolin polarity and cell directional migration
FEBS Letters, 2009Co-Authors: Hong Chen, Andrew R. Beardsley, Qi QiAbstract:Caveolin-1 (Cav-1) plays an important role in the organization of signaling molecules involved in a variety of signaling pathways, including those mediating cell motility. Here we show that amino acids K47–K57 of Cav-1 are a highly conserved sequence in Cav-1 and Cav-3 proteins, and that Expression of either K47–K57 deletion Cav-1 mutant or wild-type Cav-2 that lacks this sequence exhibits a non-polarized distribution Pattern. Expression of K47–K57 in Cav-2 leads to Cav-2 polarity, suggesting that Expression of K47–K57 is sufficient to direct caveolin polarity. Importantly, we show that Expression of this sequence is both necessary and sufficient to promote cell directional migration. Thus, our results support the conclusion that Cav-1 polarity is critical for cell directional migration.
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A conserved sequence in caveolin‐1 is both necessary and sufficient for caveolin polarity and cell directional migration
FEBS Letters, 2009Co-Authors: Hong Chen, Andrew R. Beardsley, Qi QiAbstract:Caveolin-1 (Cav-1) plays an important role in the organization of signaling molecules involved in a variety of signaling pathways, including those mediating cell motility. Here we show that amino acids K47–K57 of Cav-1 are a highly conserved sequence in Cav-1 and Cav-3 proteins, and that Expression of either K47–K57 deletion Cav-1 mutant or wild-type Cav-2 that lacks this sequence exhibits a non-polarized distribution Pattern. Expression of K47–K57 in Cav-2 leads to Cav-2 polarity, suggesting that Expression of K47–K57 is sufficient to direct caveolin polarity. Importantly, we show that Expression of this sequence is both necessary and sufficient to promote cell directional migration. Thus, our results support the conclusion that Cav-1 polarity is critical for cell directional migration.
Junying Zhang - One of the best experts on this subject based on the ideXlab platform.
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Pattern Expression nonnegative matrix factorization algorithm and applications to blind source separation
Computational Intelligence and Neuroscience, 2008Co-Authors: Junying Zhang, Xuerong Feng, Yue WangAbstract:Independent component analysis (ICA) is a widely applicable and effective approach in blind source separation (BSS), with limitations that sources are statistically independent. However, more common situation is blind source separation for nonnegative linear model (NNLM) where the observations are nonnegative linear combinations of nonnegative sources, and the sources may be statistically dependent. We propose a Pattern Expression nonnegative matrix factorization (PE-NMF) approach from the view point of using basis vectors most effectively to express Patterns. Two regularization or penalty terms are introduced to be added to the original loss function of a standard nonnegative matrix factorization (NMF) for effective Expression of Patterns with basis vectors in the PE-NMF. Learning algorithm is presented, and the convergence of the algorithm is proved theoretically. Three illustrative examples on blind source separation including heterogeneity correction for gene microarray data indicate that the sources can be successfully recovered with the proposed PE-NMF when the two parameters can be suitably chosen from prior knowledge of the problem.
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Blind Source Separation with Pattern Expression NMF
Lecture Notes in Computer Science, 2006Co-Authors: Junying Zhang, Zhang Hong-yi, Le Wei, Yue Joseph WangAbstract:Independent component analysis (ICA) is a widely applicable and effective approach in blind source separation (BSS) for basic ICA model, but with limitations that sources should be statistically independent, while more common situation is BSS for non-negative linear (NNL) model where observations are linear combinations of non-negative sources with non-negative coefficients and sources may be statistically dependent. By recognizing the fact that BSS for basic ICA model corresponds to matrix factorization problem, in this paper, a novel idea of BSS for NNL model is proposed that the BSS for NNL come'[ sponds to a non-negative matrix factorization problem and the non-negative matrix factorization (NMF) technique is utilized. For better Expression of the Patterns of the sources, the NMF is further extended to Pattern Expression NMF (PE-NMF) and its algorithm is presented. Finally, the experimental results are presented which show the effectiveness and efficiency of the PE-NMF to BSS for a variety of applications which follow NNL model.
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ISNN (1) - Blind source separation with Pattern Expression NMF
Advances in Neural Networks - ISNN 2006, 2006Co-Authors: Junying Zhang, Zhang Hong-yi, Le Wei, Yue Joseph WangAbstract:Independent component analysis (ICA) is a widely applicable and effective approach in blind source separation (BSS) for basic ICA model, but with limitations that sources should be statistically independent, while more common situation is BSS for non-negative linear (NNL) model where observations are linear combinations of non-negative sources with non-negative coefficients and sources may be statistically dependent. By recognizing the fact that BSS for basic ICA model corresponds to matrix factorization problem, in this paper, a novel idea of BSS for NNL model is proposed that the BSS for NNL corresponds to a non-negative matrix factorization problem and the non-negative matrix factorization (NMF) technique is utilized. For better Expression of the Patterns of the sources, the NMF is further extended to Pattern Expression NMF (PE-NMF) and its algorithm is presented. Finally, the experimental results are presented which show the effectiveness and efficiency of the PE-NMF to BSS for a variety of applications which follow NNL model.
Doris Cerecedo - One of the best experts on this subject based on the ideXlab platform.
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Role of α-Dystrobrevin in the differentiation process of HL-60 cells.
Experimental Cell Research, 2018Co-Authors: Ivette Martínez-vieyra, Giselle Pacheco-tapia, César A. Reyes-lópez, J.v. Méndez-méndez, Doris CerecedoAbstract:The α-Dystrobrevin gene encodes at least five different protein isoforms, expressed in diverse tissues. The α-Dystrobrevin-1 isoform (α-Db-1) is a member of the cytoplasmic dystrophin-associated protein complex, which has a C-terminal extension comprising at least three tyrosine residues susceptible to phosphorylation in vivo. We previously described α-Db in stem-progenitor cells and blood neutrophils as playing a scaffolding role and, in association with kinesin and microtubules, α-Db promotes platelet-granule trafficking. Additionally, the microtubules must establish a balanced interaction with the lamina A/C network for appropriate nuclear morphology. Considering that the most outstanding feature during neutrophil differentiation is nuclei lobulation, we hypothesized that α-Db might possess a pivotal function during the neutrophil differentiation process. Western Blot (WB) and confocal microscope assays evidenced a differential Pattern Expression and a subcellular redistribution of α-Db in neutrophils derived from HL-60 cells. At the end of the differentiation process, we detected an important diminution in the Expression of tubulin, kinesin, and α-Db-1. Knockdown of α-Db prevented nuclei lobulation, increased Lamin A/C and syne1 Expression and augmented the roughness of derived neutrophil membrane and disturbed filopodia assembly. Our results suggest that HL-60 cells undergo extensive cytoskeletal reorganization including α-Db in order to possess lobulated nuclei when they further differentiate into neutrophils.
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distribution of dystrophin and utrophin associated protein complexes dapc uapc in human hematopoietic stem progenitor cells
European Journal of Haematology, 2011Co-Authors: Carmen Tenientede Alba, Iván J. Galván, Bulmaro Cisneros, Ivette Martinezvieyra, Raul Vivancocalixto, Doris CerecedoAbstract:Hematopoietic stem cells (HSC) are defined by their cardinal properties, such as sustained proliferation, multilineage differentiation, and self-renewal, which give rise to a hierarchy of progenitor populations with more restricted potential lineage, ultimately leading to the production of all types of mature blood cells. HSC are anchored by cell adhesion molecules to their specific microenvironment, thus regulating their cell cycle, while cell migration is essentially required for seeding the HSC of the fetal bone marrow (BM) during development as well as in adult BM homeostasis. The dystrophin-associated protein complex (DAPC) is a large group of membrane-associated proteins linking the cytoskeleton to the extracellular matrix and exhibiting scaffolding, adhesion, and signaling roles in muscle and non-muscle cells including mature blood cells. Because adhesion and migration are mechanisms that influence the fate of the HSC, we explored the presence and the feasible role of DAPC. In this study, we characterized the Pattern Expression by immunoblot technique and, by confocal microscopy analysis, the cellular distribution of dystrophin and utrophin gene products, and the dystrophin-associated proteins (α-, β-dystroglycan, α-syntrophin, α-dystrobrevin) in relation to actin filaments in freshly isolated CD34+ cells from umbilical cord blood. Immunoprecipitation assays demonstrated the presence of Dp71d/Dp71Δ110m ∼DAPC and Up400/Up140∼DAPC. The subcellular distribution of the two DAPC in actin-based structures suggests their dynamic participation in adhesion and cell migration. In addition, the particular protein Pattern Expression found in hematopoietic stem/progenitor cells might be indicative of their feasible participation during differentiation.
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Distribution of dystrophin- and utrophin-associated protein complexes during activation of human neutrophils
Experimental hematology, 2010Co-Authors: Doris Cerecedo, Bulmaro Cisneros, Pablo Gomez, Iván J. GalvánAbstract:Objective. Dystrophins, utrophins, and their associated proteins are involved in structural and signaling roles in nonmuscle tissues; however, description of these proteins in neutrophils remained unexplored. Therefore we characterize the Pattern Expression, and the cellular distribution of dystrophin and utrophin gene products and dystrophin-associated proteins (i.e., b-dystroglycan, a-syntrophin, and a-dystrobrevins) in relation to actin filaments in resting and activated with formyl-methionyl-leucyl-phenylalanine human neutrophils. Materials and Methods. Resting and fMLP-activated human neutrophils were analyzed by immunoblot and by confocal microscopy analysis. Immunoprecipitation assays were performed to corroborate the presence of protein complexes. Results. Immunoprecipitation assays and confocal analysis demonstrated the presence of two dystrophin-associated protein complexes in resting and activated neutrophils: the former formed by Dp71d/Dp71D110 m and dystrophin-associated proteins (b-dystroglycan, a-syntrophin, a-dystrobrevin-1, and -2), while the latter contains Up400, instead of Dp71d/Dp71D110 m , as a central component of the dystrophin-associated protein complexes (DAPC). Confocal analysis also showed the subcellular redistribution of Dp71d/Dp71D110 m wDAPC and Up400w DAPC in F-actinLbased structures displayed during activation process with fMLP. Conclusions. Our study showed the existence of two protein complexes formed by Dp71d/ Dp71D110 m or Up400 associated with DAPs in resting and fMLP-treated human polymorpho
Hong Chen - One of the best experts on this subject based on the ideXlab platform.
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A conserved sequence in caveolin‐1 is both necessary and sufficient for caveolin polarity and cell directional migration
FEBS Letters, 2009Co-Authors: Hong Chen, Andrew R. Beardsley, Qi QiAbstract:Caveolin-1 (Cav-1) plays an important role in the organization of signaling molecules involved in a variety of signaling pathways, including those mediating cell motility. Here we show that amino acids K47–K57 of Cav-1 are a highly conserved sequence in Cav-1 and Cav-3 proteins, and that Expression of either K47–K57 deletion Cav-1 mutant or wild-type Cav-2 that lacks this sequence exhibits a non-polarized distribution Pattern. Expression of K47–K57 in Cav-2 leads to Cav-2 polarity, suggesting that Expression of K47–K57 is sufficient to direct caveolin polarity. Importantly, we show that Expression of this sequence is both necessary and sufficient to promote cell directional migration. Thus, our results support the conclusion that Cav-1 polarity is critical for cell directional migration.
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A conserved sequence in caveolin‐1 is both necessary and sufficient for caveolin polarity and cell directional migration
FEBS Letters, 2009Co-Authors: Hong Chen, Andrew R. Beardsley, Qi QiAbstract:Caveolin-1 (Cav-1) plays an important role in the organization of signaling molecules involved in a variety of signaling pathways, including those mediating cell motility. Here we show that amino acids K47–K57 of Cav-1 are a highly conserved sequence in Cav-1 and Cav-3 proteins, and that Expression of either K47–K57 deletion Cav-1 mutant or wild-type Cav-2 that lacks this sequence exhibits a non-polarized distribution Pattern. Expression of K47–K57 in Cav-2 leads to Cav-2 polarity, suggesting that Expression of K47–K57 is sufficient to direct caveolin polarity. Importantly, we show that Expression of this sequence is both necessary and sufficient to promote cell directional migration. Thus, our results support the conclusion that Cav-1 polarity is critical for cell directional migration.
